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solve_image_captcha

Read distorted characters from a captcha image URL or base64 and return them as text, so agents can complete forms requiring manual captcha entry.

Instructions

Read the characters in an image captcha given as base64 or a URL and return them as text. Use when a form shows a picture of distorted characters you will type yourself; for a challenge widget on a blocked page use solve_and_continue. Returns text, or a taskId to follow with captcha_status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imageYesThe captcha image, as base64 or as a URL.
is_base64NoSay so when `image` is base64 and could be mistaken for a URL.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.3

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations only declare readOnlyHint=false and openWorldHint=false, so the description carries the interesting burden. It discloses the return shape ("Returns `text`, or a `taskId` to follow with captcha_status"), which reveals the async possibility and the follow-up tool, adding real behavioral value. It does not discuss rate limits or failure behavior, so it falls short of a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tightly packed sentences: purpose, then usage routing, then return values. Nothing is redundant and the discriminating usage guidance is front-loaded after the core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description appropriately explains the return values (text or taskId plus the follow-up tool). Combined with full schema coverage and clear routing, an agent has everything needed to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so both parameters are already documented, giving a baseline of 3. The description restates that the image may be base64 or a URL but adds no format, size, or encoding detail beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: read characters in an image captcha and return them as text. It explicitly distinguishes itself from solve_and_continue, which handles challenge widgets on blocked pages, so an agent can disambiguate without opening either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides a concrete when-to-use condition ("a form shows a picture of distorted characters you will type yourself") and an explicit alternative with its own trigger ("for a challenge widget on a blocked page use solve_and_continue"). Routing is unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.